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连续拓扑变化下无标度网络上合作的稳健性。

Robustness of cooperation on scale-free networks under continuous topological change.

作者信息

Ichinose Genki, Tenguishi Yuto, Tanizawa Toshihiro

机构信息

Department of Systems and Control Engineering, Anan National College of Technology, 265 Aoki Minobayashi, Anan, Tokushima 774-0017, Japan.

Department of Electrical Engineering and Information Science, Kochi National College of Technology, 200-1 Monobe-Otsu, Nankoku, Kochi 783-8508, Japan.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Nov;88(5):052808. doi: 10.1103/PhysRevE.88.052808. Epub 2013 Nov 13.

DOI:10.1103/PhysRevE.88.052808
PMID:24329319
Abstract

In this paper, we numerically investigate the robustness of cooperation clusters in prisoner's dilemma played on scale-free networks, where the network topologies change by continuous removal and addition of nodes. Each removal and addition can be either random or intentional. We therefore have four different strategies in changing network topology: random removal and random addition (RR), random removal and preferential addition (RP), targeted removal and random addition (TR), and targeted removal and preferential addition (TP). We find that cooperation clusters are most fragile against TR, while they are most robust against RP, even for large values of the temptation coefficient for defection. The effect of the degree mixing pattern of the network is not the primary factor for the robustness of cooperation under continuous change in network topology, which is quite different from the cases observed in static networks. Cooperation clusters become more robust as the number of links of hubs occupied by cooperators increase. Our results might infer the fact that a huge variety of individuals is needed for maintaining global cooperation in social networks in the real world where each node representing an individual is constantly removed and added.

摘要

在本文中,我们通过数值方法研究了在无标度网络上进行的囚徒困境博弈中合作簇的鲁棒性,其中网络拓扑结构通过连续地移除和添加节点而发生变化。每次移除和添加可以是随机的,也可以是有针对性的。因此,我们在改变网络拓扑结构时有四种不同的策略:随机移除和随机添加(RR)、随机移除和优先添加(RP)、靶向移除和随机添加(TR)以及靶向移除和优先添加(TP)。我们发现,合作簇对TR最为脆弱,而对RP最为鲁棒,即使对于背叛诱惑系数的较大值也是如此。在网络拓扑结构持续变化的情况下,网络的度混合模式的影响并非合作鲁棒性的主要因素,这与在静态网络中观察到的情况有很大不同。随着合作者占据的中心节点的链接数量增加,合作簇会变得更加鲁棒。我们的结果可能推断出这样一个事实,即在现实世界的社交网络中,为了维持全球合作,需要各种各样的个体,其中每个代表个体的节点都在不断地被移除和添加。

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